Semantic Annotation Interface Generation for AI Algorithm Integration
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Solution Overview
Problem
Existing software tools for developing artificial intelligence algorithms are not suitable for creating technology-agnostic interfaces that can integrate these algorithms directly into customer applications and processes, and they do not allow for the concealment of source code from customers.
Innovation Solution
A method and computer program that utilize a library of semantic annotations to automatically generate communication interfaces, such as REST interfaces, for integrating artificial intelligence algorithms into customer applications. This method involves analyzing the source text for semantic annotations, generating logic sequences for interface creation, and embedding these interfaces into a computer program product.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual reworking of source text is performed to add communication interfaces, then customer applications can integrate algorithms, but development time and complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-defining semantic annotations in the source code that mark algorithm constructs and their interfaces. These annotations are prepared in advance during algorithm development, so that when productization is needed, the communication interface generator can automatically process them without manual reworking. This resolves the contradiction by having the integration准备工作 done upfront, eliminating time-consuming manual interface addition later.
Solution Approach 2:
The patent implements self-service through the automatic generation of communication interfaces from annotated source code. The system generates the necessary interface code, validation logic, and documentation automatically based on the semantic annotations present in the source text, eliminating the need for manual intervention by software developers. This resolves the contradiction by enabling self-service interface generation that maintains adaptability while reducing development time.
2Reliability
If source text is concealed from customers via API interfaces, then intellectual property is protected, but customization and troubleshooting capability are reduced
Solution Approach 1:
The patent uses semantic annotations as an intermediary layer between the source code and the communication interface. The annotations contain metadata about algorithm parameters, data structures, and expected inputs/outputs, allowing the system to generate interfaces that expose necessary customization points while keeping the core algorithm source code concealed. This resolves the contradiction by providing an intermediary mechanism that enables customer customization and troubleshooting through well-defined interfaces without revealing proprietary source text.
Solution Approach 2:
The patent enables parameter changes by allowing customers to modify algorithm behavior through the generated interfaces without accessing or modifying the source code. The semantic annotations define configurable parameters and data structures that can be adjusted via the API, allowing customization and troubleshooting while maintaining IP protection. This resolves the contradiction by separating the immutable source code from the configurable parameters accessible through interfaces.
3Reliability
If specialized software developers are involved in transferring algorithms to products, then interface quality is ensured, but development costs and complexity increase
Solution Approach 1:
The patent implements self-service by enabling automated generation of communication interfaces from annotated source code. The system automatically creates interface code, validation logic, error handling, and documentation based on the semantic annotations, eliminating the need for specialized software developers to manually create these interfaces. This resolves the contradiction by providing self-service interface generation that ensures quality through systematic processing while reducing development process complexity and costs.
Solution Approach 2:
The patent changes the development model from manual interface creation to automated parameter-based generation. By defining algorithms with semantic annotations that specify interface requirements, the system automatically generates appropriate interfaces without requiring specialized developer intervention. This resolves the contradiction by transforming the complex manual process into a simpler automated parameter-driven process that maintains interface quality while reducing complexity.
4Reliability
If comprehensive validation and error handling are added to source text, then interface reliability is improved, but source text complexity and maintenance burden increase
Solution Approach 1:
The patent extracts validation and error handling logic from the source code into separate generated interface components. The semantic annotations enable the system to automatically generate validation rules, error handling code, and data structure verification in the generated interface layer, keeping the original source text clean and simple. This resolves the contradiction by extracting reliability-enhancing code from the source text into automatically generated interface components that do not burden the original code with complexity.
Solution Approach 2:
The patent applies preliminary action by pre-defining validation requirements and error handling specifications through semantic annotations in the source code. These annotations capture the intended validation logic and error handling requirements upfront, allowing the system to automatically generate comprehensive validation and error handling code during interface generation without adding complexity to the source text. This resolves the contradiction by performing validation setup in advance through annotations rather than adding complex validation code to the source text itself.
Data Source
AI summary
A computer program and method for producing a further computer program product starting from a source text of artificial intelligence algorithms with the following steps: a) providing a library of semantic annotations; b) analyzing the source text with a source text analysis component for the presence of the semantic annotations in the source text; c) generating a communication interface with a communication interface generator; d) analyzing the source text for the presence of a semantic annotation in the source text and transferring the logic sequence from the library that is uniquely linked to the semantic annotation to the communication interface generator; e) reading the logic sequence that has been transferred and is linked to the semantic annotation present in the source text, and f) generating a communication interface on the basis of the logic sequence; and g) embedding the generated communication interface in the computer program product.
